OBSCURE PHENOMENA IN STATISTICAL-ANALYSIS OF QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS .1. MULTICOLLINEARITY OF PHYSICOCHEMICAL DESCRIPTORS

被引:0
作者
MAGER, PP [1 ]
ROTHE, H [1 ]
机构
[1] UNIV JENA,TECH SECT,O-6900 JENA,GERMANY
来源
PHARMAZIE | 1990年 / 45卷 / 10期
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中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Multicollinearity of physiocochemical descriptors lease to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.
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页码:758 / 764
页数:7
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